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A BL-MF fusion model for portfolio optimization: Incorporating the Black–Litterman solution into multi-factor model

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Listed:
  • Yuan, Jin
  • Jin, Liwei
  • Lan, Feng

Abstract

We study a Black–Litterman and multi-factor (BL-MF) fusion model that integrates equilibrium expected returns and investor views information from the Black–Litterman framework with the return-factor correlation information captured in the multi-factor model. The optimal estimator derived from our model improves accuracy in estimating expected returns and covariance matrix. We build optimal portfolios using our BL-MF model and benchmarks, adhering to both standard and criteria tailored for capturing tail risk with non-normal return distributions. Out-of-sample tests show our BL-MF portfolios outperform various benchmarks, and robustness checks validate this performance advantage, regardless of changes in sub-period, estimation window length or data frequency.

Suggested Citation

  • Yuan, Jin & Jin, Liwei & Lan, Feng, 2025. "A BL-MF fusion model for portfolio optimization: Incorporating the Black–Litterman solution into multi-factor model," Finance Research Letters, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:finlet:v:80:y:2025:i:c:s1544612325007238
    DOI: 10.1016/j.frl.2025.107464
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    References listed on IDEAS

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    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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